We train a single \(\mathsf {CAE}\)  model for all tested \(\mathsf {SNR}\)  values.
We use AdamW optimizer [1]} that runs back-propagation to optimize the model during training. AdamW is designed such that it improves gradients when using \(\text{L}_2\)  regularization.
